Getting Started

Daeploy consists of two components, a software development kit (SDK) and a manager application that runs on the target machine. The SDK is a python library that you use in your code to make into a service and the manager helps you deploy your code into running applications.


To use Daeploy, you need to have python >= 3.6 installed in your development environment and docker in your deployment environment.


The Daeploy python library can be installed with pip:

>>> pip install daeploy  

Check your installation by running: daeploy --help in a terminal.

You will also need a manager container. To start a manager running on localhost for development, run the following command:

>>> docker run -v /var/run/docker.sock:/var/run/docker.sock -p 80:80 -p 443:443 -d daeploy/manager:latest  

You can check that it started correctly by opening http://localhost/ in your browser.


This configuration should never be used in production. It is missing crucial features such as authentication and secured communication. Please refer to Manager Configuration for an example of a production setup.

Deploying Your First Service

Once the Manager is up and running you are ready to start using Daeploy. The fastest and easiest way to interact with the Manager is to use the Command-line Interface (CLI) that comes packaged with the SDK. The CLI contains a host of useful commands that make the deployment and monitoring of services fast and painless.


You can call daeploy --help at any time, to get a list and short description of the available commands and daeploy <COMMAND> --help to get a longer description of that command.

Logging in to the Manager

The first step is to login to the host where Daeploy is running, if you started the manager with the command above, your host is http://localhost. To do this, we call the daeploy login command. If the manager has authentication enabled, you will be prompted for a username and password.

>>> daeploy login  
Enter Daeploy host: http://localhost

Once you have logged in you are connected to your specified host and able to communicate with the Manager running there. Logins last for a week, before you have to login again. We can check if we are logged in by calling:

>>> daeploy ls 
------  ------  ---------  --------  ---------

It should return an empty list. If you didn’t log in, you would get this message:

>>> daeploy ls 
You must log in to a Daeploy host with `daeploy login` before using this command.

Creating a New Service

When creating a new service we recommend the user to create a project template with:

>>> daeploy init 
project_name [my_project]: my_first_daeploy_project

This creates a new directory called my_first_daeploy_project in your current working directory. Let’s see what’s in it:

>>> ls -a ./my_first_daeploy_project  
.  ..  .s2i/  .s2iignore  requirements.txt  tests/

Let’s not worry about the individual files and directories. For now it is enough to know that my_first_daeploy_project contains a fully functioning hello world service that we can deploy straight away.

Deploying the Service

The CLI has a command to deploy a service. It requires that you to give it a name and version and then specify the path to the project directory.

>>> daeploy deploy my_first_service 0.0.1 ./my_first_daeploy_project  
Deploying service...
Service deployed successfully
------  ----------------  ---------  --------  -----------------------------------
*       my_first_service  0.0.1      running   Running (since 2020-11-20 15:48:45)

After a few seconds the service should be up and running. We can check with daeploy ls that it started properly.

>>> daeploy ls 
------  ----------------  ---------  --------  -----------------------------------
*       my_first_service  0.0.1      running   Running (since 2020-11-20 15:48:45)

If you open http://localhost in a browser you should see the dashboard where you can get much of the same information as through the CLI. And at http://localhost/services/my_first_service_0.0.1/docs you can read the automated API documentation of the service and test its functionality.


To communicate with your services from outside of the documentation you can use any HTTP library, which are available in most programming languages. In python requests is commonly used or curl in bash.

Killing a Service

Say that you are finished with your service, then the process can be stopped and the service removed by calling:

>>> daeploy kill my_first_service 0.0.1  
------  ----------------  ---------  --------  -----------------------------------
*       my_first_service  0.0.1      running   Running (since 2020-11-20 15:48:45)
Are you sure you want to kill the above service(s)? [y/N]: y
Service my_first_service 0.0.1 killed.

What’s next?

Now that you know the basics of how to deploy a service using the CLI it might be time to learn how to write your own service: Anatomy of a Service, or maybe take a look at the Command-line Interface documentaion.